Models and pricing

Two surfaces are billed: agentic skills (per token, by the model in skill.yaml) and media generation (per call / second / megapixel, by the model slug you pass to media.run()). Deterministic Python skills are free at the platform level — you only pay for what they call into.

Money is tracked in MICROS (1 USD = 1,000,000 micros); the dashboard and API responses convert back to dollars.

Agentic skill models

The model: field in skill.yaml is a public slug in family/variant form. Use one of:

# skills/my-skill/skill.yaml
model: claude/sonnet-4-7

Three families are available — Claude, GPT, and Gemini. Pick by need; you don't need to know how each one is served.

Claude — prices

Per 1 million tokens, rounded to the cent.

Vision and PDF attachments are supported on every Claude slug above. See agent-attachments for how attachments flow through.

GPT — prices

Per 1 million tokens, rounded to the cent.

Vision (image) attachments supported. PDF attachments are not supported — convert pages to images first.

Gemini — prices

Per 1 million tokens, rounded to the cent.

Vision (image) attachments supported. PDF attachments are not supported — convert pages to images first.

Indicative rates. Final cost per job is shown on the job detail page based on the actual tokens used.

Defaults and fallbacks

• If model: is omitted from skill.yaml, the platform default is used (claude/sonnet-4-6 today). The fallback is stable per deployment — you'll see it on the agent_start event.
• Unknown slugs are rejected at deploy time with a clear error listing the available slugs.

Media generation

media.run(model, inputs) invokes any model we have a registered cost for. The full catalog of slugs and their rates is the pricing page or GET /v1/pricing. Cost is static per model — unknown slugs are rejected with HTTP 400 (so a request can't slip through unpriced).

Four pricing shapes — most models use exactly one:

Cost is debited at job-completion time and shown on the job detail page.

Most model families ship multiple slugs — one per variant. The naming convention:

• -t2v, -i2v, -r2v → text-to-video, image-to-video, reference-to-video
• -edit → image-to-image edit
• -fast- segment → the fast tier of that variant (lower per-second rate, slightly lower quality)

Example

from puras import media

# Per-call image, default high@1024x1024
img = media.run("openai/gpt-image-2", {"prompt": "a red bicycle"})

# Cheap edit
cheap = media.run("bytedance/seedream-v4-edit", {
    "image_url": img["output_url"],
    "prompt": "make it neon",
})

# Per-second video with audio on (billed at the audio-on rate)
clip = media.run("google/veo-3-t2v", {"prompt": "...", "duration": 5, "generate_audio": True})

# Image-to-video, fast tier
vid = media.run(
    "bytedance/seedance-2-fast-i2v",
    {"image_url": img["output_url"], "prompt": "spin slowly", "duration": 8},
)

The dashboard's Usage tab breaks down spend by model for every billable call so you can see exactly what cost what.

Free things

• Function execution (deterministic Python skills) and worker time.
• Drive uploads / signed URLs / list calls.
• MCP server, dashboard, API key checks.
• web_search, image_search, web_fetch, download_url, bash, file_read agent tools at the platform level (you only pay for what they trigger — e.g. a media.run inside a tool is billed normally).

Conventions

• Default to Sonnet unless you have a reason. Opus's premium pays off for genuinely hard reasoning; Haiku and the mini tiers shine for narrow, structured tools where you can keep the prompt tight.
• Budget caps live on the project, not the skill. A runaway agent will burn the project's balance, not just one skill's. Set per-project balance limits in the dashboard.

See concepts for how usage rolls up into the billing surface, and sdk-media for the full media.run contract.